Collection development or data-driven content curation? An exploratory project in Manchester

Publication Date13 June 2016
AuthorRachel Joy Kirkwood
SubjectLibrary & information science,Librarianship/library management,HR in libraries
Collection development or
data-driven content curation?
An exploratory project
in Manchester
Rachel Joy Kirkwood
University of Manchester, Manchester, UK
Purpose Collection development in a post-subject librarian age needs to be done differently; utilising
data, metadata, analytical tools and automation more fully may offer new possibilities. The purpose of
this paper is to report and evaluate an exploratory project into new techniques for collection
development at the University of Manchester Library.
Design/methodology/approach The project employed a cross-team approach where a relatively
large number of staff tried some innovative and experimental approaches to individual aspects of a
large and complex task in a large, research-intensive university library. The overriding aim was to
exploit data to support decision making and to push automation as far as possible.
Findings The quality of (meta)data remains a huge hindrance to data-driven approaches. A proper
understanding of usage data is an urgent but intractable issue. Human input and relationships are still
important. Data are nothing without analysis, and many librarians currently lack the data fluency to
work confidently in a world of dynamic content curation.
Practical implications Librarians need both to re-skill and to change their self-identification and
the philosophy that underlies it if they are to achieve confident, data fluency.
Originality/value The University of Manchester Library was one of the first libraries in the UK to
make a thoroughgoing structural change from subject-based to functional teams. This paper will be of
value to other libraries moving in this direction, and to those looking to make more use of data-driven
decision making in collections management.
Keywords Collection development, Librarianship, Libraries, Collections strategy,
Cooperative collections ventures, Data-driven content curation
Paper type Viewpoint
1. Introduction
The University of Manchester is big. With around 350 staff and over four million items,
size is one of its defining characteristics. The Library is ambitious and innovative, and
less risk-averse than some other HE libraries. A major review and restructure of the
former Research & Learning Supportdivision in 2012/2013 positioned librarians to
up-skill and specialise to meet new challenges, organising staff into functional teams
and doing away with the traditional subject librarian model, with its broad spread of
activities not least of which was book selection.
After a year of the new structure bedding in, a vacuum in collection development
was identified. The disappearance of the subject librarians created a managerial
challenge for the curation of our similarly large collections, to which pragmatic
solutions were needed. The feasibility and efficacy of a research resources robotwas
humorously hypothesised, and a major library strategy project was designed, the
overall aim of which was to experiment with what can be done with data and how far
automation can be employed in the services of collection development at a large,
Library Management
Vol. 37 No. 4/5, 2016
pp. 275-284
©Emerald Group Publis hing Limited
DOI 10.1108/LM-05-2016-0044
Received 13 February 2016
Revised 16 May 2016
Accepted 16 May 2016
The current issue and full text archive of this journal is available on Emerald Insight at:
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